title: Variation at diabetes- and obesity-associated Loci may mirror neutral patterns of human population diversity and diabetes prevalence in India.
abstract: South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes- and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.
authors.affiliation: Department of Molecular Biology and Genetics, 101 Biotechnology Building, Cornell University, Ithaca, NY, 14853, USA; Division of Biological Anthropology, Henry Wellcome Building, Fitzwilliam Street, Cambridge, CB2 1QH, UK.
authors.forename: Srilakshmi M
authors.initials: SM
authors.lastname: Raj
authors.forename: Pradeep
authors.initials: P
authors.lastname: Halebeedu
authors.forename: Jayarama S
authors.initials: JS
authors.lastname: Kadandale
authors.forename: Marta
authors.initials: M
authors.lastname: Mirazon Lahr
authors.forename: Irene
authors.initials: I
authors.lastname: Gallego Romero
authors.forename: Jamuna R
authors.initials: JR
authors.lastname: Yadhav
authors.forename: Mircea
authors.initials: M
authors.lastname: Iliescu
authors.forename: Niraj
authors.initials: N
authors.lastname: Rai
authors.forename: Federica
authors.initials: F
authors.lastname: Crivellaro
authors.forename: Gyaneshwer
authors.initials: G
authors.lastname: Chaubey
authors.forename: Richard
authors.initials: R
authors.lastname: Villems
authors.forename: Kumarasamy
authors.initials: K
authors.lastname: Thangaraj
authors.forename: Kalappagowda
authors.initials: K
authors.lastname: Muniyappa
authors.forename: H Sharat
authors.initials: HS
authors.lastname: Chandra
authors.forename: Toomas
authors.initials: T
authors.lastname: Kivisild
mesh_terms: D000483:Alleles; D003920:Diabetes Mellitus / Q000453:epidemiology* / Q000235:genetics*; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology / Q000235:genetics; D005787:Gene Frequency; D056426:Genetic Loci; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D005838:Genotype; D006801:Humans; D007194:India / Q000453:epidemiology; D009765:Obesity / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D015995:Prevalence
keywords: Human genetic variation; India; obesity; population genetics; type 2 diabetes